Search Results for author: Alexander N. Tait

Found 5 papers, 1 papers with code

Demonstration of Superconducting Optoelectronic Single-Photon Synapses

no code implementations20 Apr 2022 Saeed Khan, Bryce A. Primavera, Jeff Chiles, Adam N. McCaughan, Sonia M. Buckley, Alexander N. Tait, Adriana Lita, John Biesecker, Anna Fox, David Olaya, Richard P. Mirin, Sae Woo Nam, Jeffrey M. Shainline

Superconducting optoelectronic hardware is being explored as a path towards artificial spiking neural networks with unprecedented scales of complexity and computational ability.

Photonics for artificial intelligence and neuromorphic computing

no code implementations30 Oct 2020 Bhavin J. Shastri, Alexander N. Tait, Thomas Ferreira de Lima, Wolfram H. P. Pernice, Harish Bhaskaran, C. David Wright, Paul R. Prucnal

Research in photonic computing has flourished due to the proliferation of optoelectronic components on photonic integration platforms.

Medical Diagnosis

Noise Analysis of Photonic Modulator Neurons

no code implementations17 Jul 2019 Thomas Ferreira de Lima, Alexander N. Tait, Hooman Saeidi, Mitchell A. Nahmias, Hsuan-Tung Peng, Siamak Abbaslou, Bhavin J. Shastri, Paul R. Prucnal

Here, we examine modulator-based photonic neuron circuits with passive and active transimpedance gains, with special attention to the sources of noise propagation.

Digital Electronics and Analog Photonics for Convolutional Neural Networks (DEAP-CNNs)

1 code implementation23 Apr 2019 Viraj Bangari, Bicky A. Marquez, Heidi B. Miller, Alexander N. Tait, Mitchell A. Nahmias, Thomas Ferreira de Lima, Hsuan-Tung Peng, Paul R. Prucnal, Bhavin J. Shastri

Convolutional Neural Networks (CNNs) are powerful and highly ubiquitous tools for extracting features from large datasets for applications such as computer vision and natural language processing.

Neuromorphic Silicon Photonic Networks

no code implementations5 Nov 2016 Alexander N. Tait, Thomas Ferreira de Lima, Ellen Zhou, Allie X. Wu, Mitchell A. Nahmias, Bhavin J. Shastri, Paul R. Prucnal

At increased scale, Neuromorphic silicon photonics could access new regimes of ultrafast information processing for radio, control, and scientific computing.

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